Moon Phases Trading Strategy

Boost your S&P 500 and Bitcoin trades. This daily strategy uses moon phases to uncover potential long entry points, with seasonal filters for improved returns.

Published · Updated · Methodology: Technical Indicators

Part of: Algorithmic & Automated Trading

  • Methodology: Technical Indicators
  • Content type: strategy
  • Timeframes: Daily
  • Markets: S&P 500, Bitcoin

Indicators used

  • Moon Phases

Source video

Decoded from: Can Moon Phases Predict Stocks? Backtests Say Yes! by Quantified Strategies — watch the original

Key timestamps:

  • 0:50 - Introduction to moon phases and stock market
  • 1:50 - Full Moon S&P 500 strategy rules
  • 2:50 - New Moon S&P 500 strategy rules
  • 3:25 - Improved S&P 500 strategy with weekday filter
  • 4:20 - Bitcoin Full Moon strategy rules
  • 5:00 - Improved Bitcoin strategy with weekday filter

Strategy overview

A moon phase strategy is calendar timing in its purest form: it times entries and exits by the lunar cycle — full moon and new moon dates — rather than by anything price itself is doing. What makes this entry worth reading is less the folklore than the input's unusual properties. The lunar calendar is exogenous and fully known years in advance, it contains zero market data, and it has no settings to tune. Unlike a moving average or an oscillator, it cannot lag price, cannot repaint, and cannot be curve-fitted at the signal level — every degree of freedom lives instead in how a date is turned into a trade.

The source is Quantified Strategies' "Can Moon Phases Predict Stocks? Backtests Say Yes!", a channel whose format is backtest-first: take a folk claim, define it mechanically, and let the equity curve answer. The video runs the question across two very different markets — the S&P 500 and Bitcoin — and treats full moon and new moon as separate hypotheses rather than one effect. It then presents, for each market, an improved variant that adds a weekday filter on top of the lunar condition.

That last step is the part worth sitting with. When a calendar effect is improved by adding a second calendar variable, the filter is doing real work, and the combined rule carries more degrees of freedom than its simplicity suggests — the classic hazard of seasonal anomalies, where the number of date-based conditions you could have tried is far larger than the number of independent lunar cycles in any sample. This page covers the concept and how the source frames it on daily bars across both markets; the specific conditions and the backtests behind the title's claim remain the video's own.

Topics

moon phases strategy · trading strategy · technical indicators · s&p 500 trading · bitcoin trading · daily trading · full moon strategy · crypto trading strategy · stock market strategy · tradingview strategy · pine script

Frequently asked questions

What is a moon phase trading strategy?

It is a calendar-based approach that times positions around lunar events — typically the full moon and the new moon — using the astronomical calendar as the signal instead of price action or a technical indicator. Because lunar dates are fixed and known in advance, the signal itself has no parameters; the design choices sit entirely in how each date maps to an entry, an exit, and a holding period.

Do moon phases actually affect the stock market?

There is no established causal mechanism, and the usual explanations — mood, sleep, and behavioural seasonality — remain hypotheses rather than findings. The honest framing is the one the source uses: treat it as a calendar anomaly to be tested on data, not a relationship to assume. Any conclusion belongs to the specific sample, market and rule set it was measured on.

Which markets does the source video look at?

Two: the S&P 500 and Bitcoin. Each is examined on daily data, with full moon and new moon handled as distinct cases for the index, and an additional variant in each market that layers a weekday filter on top of the lunar condition.

How should I evaluate a calendar-based strategy like this one?

Count the conditions before you count the returns. A lunar cycle produces roughly a dozen occurrences a year, so even decades of history yield a modest number of independent events — and adding a weekday filter multiplies the variants that could have been tested while shrinking the trades that survive. Insist on a long sample, an out-of-sample period the rules never saw, and realistic costs. Strategy Decoder catalogues strategies like this one from their video sources so you can identify the concept and test it yourself on TradingView before committing capital.

About this strategy page

This trading strategy was decoded by Strategy Decoder's AI from a public YouTube trading video and turned into a structured, reviewable specification. In the interactive app this page shows the full entry and exit logic, risk management settings, the indicators involved with their parameters, AlgoWizard-compatible logic and a Pine Script export ready for TradingView backtesting — plus an automated backtest verdict when one has been computed for this strategy.

Strategy Decoder catalogs 2,229 decoded strategies. Each one is extracted with confidence scoring, cross-linked to the indicators it uses, and kept up to date as new videos are processed daily. Load this page with JavaScript enabled to use the interactive tools, or start from the strategy explorer to filter by methodology, market and timeframe.

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